Synthetic chromatogram from physical properties

Patent metadata

Field	Value
Publication number	US-10570733-B2
Application number	US-201615369300-A
Country	US
Kind code	B2
Filing date	Dec 5, 2016
Priority date	Dec 5, 2016
Publication date	Feb 25, 2020
Grant date	Feb 25, 2020

Abstract

A method for estimating a chemical composition of hydrocarbons of interest includes: performing a measurement for each physical property of a plurality of physical properties of the hydrocarbons of interest using a sensor to provide a value for each different physical property being measured; and estimating the chemical composition of the hydrocarbons of interest by using a correlation prediction function for each chemical component in the chemical composition in terms of the different physical properties being measured.

First claim

What is claimed is:

1. A method for estimating a concentration of a chemical component of a crude oil of interest, the method comprising:
performing a measurement for each physical property of a plurality of physical properties of the crude oil of interest using a sensor to provide a value for each different physical property being measured;
generating, by a processor, a correlation prediction function for the chemical component in terms of the different physical properties being measured, the correlation prediction function comprising multiple composite linearly independent variables derived from the different physical properties; and
estimating, by the processor, the concentration of the chemical component of the crude oil of interest by using the correlation prediction function with the measured value of the different physical properties being measured being input into the correlation prediction function;
wherein the chemical component comprises at least one of methane (C1), ethane (C2), propane (C3), butane (C4), pentane (C5), hexane (C6), and a combination of heptane and any higher carbon number (C7+).

2. The method according to claim 1 , wherein generating the correlation prediction function comprises:
obtaining a plurality of measurements of values of different physical properties of samples of different hydrocarbons at reservoir temperatures and pressures, each sample having a known concentration of the chemical component, to serve as a training set;
generating a plurality of composite linearly independent variables comprising two or more variables corresponding to the physical properties of the samples being measured; and
performing a regression on the training set for dependent variables representing the concentration of the chemical component of the hydrocarbons at the reservoir temperatures and pressures in terms of the composite linearly independent variables so as to develop the correlation prediction function that uses measured values of the different physical properties as input to predict the concentration of the chemical component of a sample of the crude oil of interest being evaluated downhole.

3. The method according to claim 2 , wherein the chemical composition comprises a relative concentration for each of two or more carbon molecules.

4. The method according to claim 3 , wherein the correlation prediction function comprises a prediction of concentration for each of the methane (C1), ethane (C2), propane (C3), butane (C4), pentane (C5), hexane (C6), and the combination of heptane and any higher carbon number (C7+).

5. The method according to claim 2 , wherein the regression comprises a step forward multiple linear regression with substitution.

6. The method according to claim 1 , wherein the composite linearly independent variables comprise terms of a multinomial expansion of variables representing the plurality of physical properties being measured.

7. The method according to claim 6 , wherein at least one variable in the multinomial expansion is a reciprocal of a physical property being measured.

8. The method according to claim 1 , wherein the plurality of physical properties comprises at least two selections from a group consisting of density, viscosity, sound speed, pressure, and temperature.

9. The method according to claim 1 , wherein the estimating is performed in real time upon receiving the measurements for each physical property in the plurality of physical properties of the crude oil of interest.

10. The method according to claim 1 , further comprising performing a hydrocarbon production action using the estimated concentration of the chemical component of the crude oil of interest.

11. The method according to claim 10 , wherein the hydrocarbon production action comprises hydraulic fracturing an earth formation containing the hydrocarbons in a selected range of depths.

12. The method according to claim 1 , further comprising conveying a carrier through a borehole penetrating the earth, wherein the sensor is disposed on the carrier and the measurement for each physical property is performed downhole.

13. An apparatus for estimating a concentration of a chemical component of crude oil of interest, the apparatus comprising:
a sensor configured to perform a measurement for each physical property in a plurality of physical properties of the crude oil of interest to provide a value for each different physical property being measured; and
a processor configured to: generate a correlation prediction function for the chemical component in terms of the different physical properties being measured, the correlation prediction function comprising multiple composite linearly independent variables derived from the different physical properties; and estimate the concentration of the chemical component of the crude oil of interest by using the correlation prediction function with the measured value of the different physical properties being measured being input into the correlation prediction function;
wherein the chemical component comprises at least one of methane (C1), ethane (C2), propane (C3), butane (C4), pentane (C5), hexane (C6), and a combination of heptane and any higher carbon number (C7+).

14. The apparatus according to claim 13 , further comprising a carrier configured to be conveyed through a borehole penetrating the earth, wherein the sensor is disposed on the carrier and is configured to perform the measurement for each physical property downhole.

15. The apparatus according to claim 14 , wherein the carrier comprises a wireline, a drill string, coiled tubing, or a slickline.

16. The apparatus according to claim 13 , wherein the sensor comprises at least two selections from a group consisting or a density sensor, a viscosity sensor, a sound speed sensor, a pressure sensor, and a temperature sensor.

17. The apparatus according to claim 13 , further comprising a user interface configured to receive a signal from the processor, the signal comprising the concentration of the chemical component of the crude oil of interest.

18. The apparatus according to claim according to claim 13 , wherein the processor is further configured to perform the following actions to generate the prediction function:
obtaining a plurality of measurements of values of different physical properties of samples of different hydrocarbons at reservoir temperatures and pressures, each sample having a known concentration of the chemical component, to serve as a training set;
generating a plurality of composite linearly independent variables comprising two or more variables corresponding to the physical properties of the samples being measured; and
performing a regression on the training set for dependent variables representing the concentration of the chemical component of the at the reservoir temperatures and pressures in terms of the composite linearly independent variables so as to develop the correlation prediction function that uses measured values of the different physical properties as input to predict the concentration of the chemical component of a sample of the crude oil of interest being evaluated downhole.

Assignees

• Difoggio Rocco
• Nieuwoudt Hermanus J
• Baker Hughes A Ge Co Llc

Inventors

• Difoggio Rocco
• Nieuwoudt Hermanus J

Classifications

• E21B49/0875

  determining specific fluid parameters · CPC title

• G16C20/20

  Identification of molecular entities, parts thereof or of chemical compositions · CPC title

• E21B47/06

  Measuring temperature or pressure · CPC title

• E21B49/08 Primary

  Obtaining fluid samples or testing fluids, in boreholes or wells · CPC title

• G16C20/70

  Machine learning, data mining or chemometrics · CPC title